{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import random,csv,datetime,json\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def load_data(localFileName):\n",
    "    with open(localFileName, mode='r') as infile:\n",
    "        reader = csv.reader(infile)\n",
    "        lookup = {row[0]: row[1].split(';') for row in reader if row}\n",
    "    return lookup\n",
    "def build_rules(items):\n",
    "    rulesAdded = {}\n",
    "    for state, adjacent in items.items():\n",
    "        for adjacentState in adjacent:\n",
    "            if adjacentState == '':\n",
    "                continue\n",
    "            rule = Rule(state, adjacentState)\n",
    "            if rule in rulesAdded:\n",
    "                rulesAdded[rule] += 1\n",
    "            else:\n",
    "                rulesAdded[rule] = 1\n",
    "    for k, v in rulesAdded.items():\n",
    "        if v != 2:\n",
    "            print(\"rule {0} is not bidirectional\".format(k))\n",
    "    return rulesAdded.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Rule:\n",
    "    def __init__(self, node, adjacent):\n",
    "        if node < adjacent:\n",
    "            node, adjacent = adjacent, node\n",
    "        self.Node = node\n",
    "        self.Adjacent = adjacent\n",
    "\n",
    "    def __eq__(self, other):\n",
    "        return self.Node == other.Node and self.Adjacent == other.Adjacent\n",
    "\n",
    "    def __hash__(self):\n",
    "        return hash(self.Node) * 397 ^ hash(self.Adjacent)\n",
    "\n",
    "    def __str__(self):\n",
    "        return self.Node + \" -> \" + self.Adjacent\n",
    "\n",
    "    def IsValid(self, genes, nodeIndexLookup):\n",
    "        index = nodeIndexLookup[self.Node]\n",
    "        adjacentNodeIndex = nodeIndexLookup[self.Adjacent]\n",
    "        return genes[index] != genes[adjacentNodeIndex]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Chromosome:\n",
    "    def __init__(self, genes, fitness):\n",
    "        self.Genes = genes\n",
    "        self.Fitness = fitness\n",
    "        \n",
    "def mutate(parent,geneSet,size):\n",
    "    childGenes = parent.Genes[:]\n",
    "    index = random.randrange(0, len(parent.Genes))\n",
    "    newGene, alternate = random.sample(geneSet, 2)\n",
    "    childGenes[index] = alternate if newGene == childGenes[index] else newGene\n",
    "    fitness = get_fitness(childGenes,rules,size)\n",
    "    return Chromosome(childGenes, fitness)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def display(candidate, startTime):\n",
    "    timeDiff = datetime.datetime.now() - startTime\n",
    "    print(\"{0}\\t{1}\\t{2}\".format(\n",
    "        ''.join(map(str, candidate.Genes)),\n",
    "            candidate.Fitness,\n",
    "            str(timeDiff)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_fitness(genes, rules, stateIndexLookup):\n",
    "    rulesThatPass = sum(1 for rule in rules if rule.IsValid(genes, stateIndexLookup))\n",
    "    return rulesThatPass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "states = load_data(\"./adjacent_states.csv\")\n",
    "rules = build_rules(states)\n",
    "optimalValue = len(rules)\n",
    "stateIndexLookup = {key: index\n",
    "        for index, key in enumerate(sorted(states))}\n",
    "colors = [\"Orange\", \"Yellow\", \"Green\", \"Red\"]\n",
    "colorLookup = {color[0]: color for color in colors}\n",
    "geneset = list(colorLookup.keys())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_best():\n",
    "    random.seed()\n",
    "    startTime = datetime.datetime.now()\n",
    "    x = [random.choice(geneset) for i in range(len(stateIndexLookup))]\n",
    "    bestParent = Chromosome(x,get_fitness(x,rules,stateIndexLookup))\n",
    "    if bestParent.Fitness >= optimalValue:\n",
    "        return bestParent\n",
    "    num = 0\n",
    "    while True:\n",
    "        num +=1\n",
    "        child = mutate(bestParent,geneset,stateIndexLookup)\n",
    "        if bestParent.Fitness > child.Fitness:\n",
    "            continue\n",
    "        else:\n",
    "            display(child,startTime)\n",
    "            if child.Fitness  >= optimalValue:\n",
    "                return (child,num)\n",
    "            bestParent = child"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ROOYOGOORYRGYROOGGGGROOOGYYRGYRRORGOOYROOGOROGGROGG\t74\t0:00:00\n",
      "ROOYOGOORYRGYROOGGGGROOOGYYRGYRRORGOOYROOROROGGROGG\t76\t0:00:00\n",
      "RORYOGOORYRGYROOGGGGROOOGYYRGYRRORGOOYROOROROGGROGG\t77\t0:00:00\n",
      "RORYOGOORYRGYROOGGGGGOOOGYYRGYRRORGOOYROOROROGGROGG\t77\t0:00:00\n",
      "RORYOGOORYRGYROOGGGGGOOOGYYRGYRRORGGOYROOROROGGROGG\t77\t0:00:00.001013\n",
      "RORYOGOORYRGYROOGGGGGOOORYYRGYRRORGGOYROOROROGGROGG\t78\t0:00:00.001013\n",
      "RORYOGOORYRGYROOGGGGROOORYYRGYRRORGGOYROOROROGGROGG\t78\t0:00:00.001013\n",
      "RORYOGOORYRGYROOGGGGROOORYYRGYRRORGGOYROOROROGGRORG\t79\t0:00:00.001013\n",
      "RORYOGOORYRGYROOGGGGROOORYYRGYRRORGGOYYOOROROGGRORG\t83\t0:00:00.001013\n",
      "RORYOGOORYRGYROOGGGGROOORYYRGYRRORGGOYYROROROGGRORG\t84\t0:00:00.001013\n",
      "RORYOGOORYRGYROOGGGGROOORYYRGYRRORGYOYYROROROGGRORG\t84\t0:00:00.001996\n",
      "RORYOGOORYYGYROOGGGGROOORYYRGYRRORGYOYYROROROGGRORG\t84\t0:00:00.001996\n",
      "RORYOGOORYYGYROOGGGGROORRYYRGYRRORGYOYYROROROGGRORG\t84\t0:00:00.001996\n",
      "RORYOYOORYYGYROOGGGGROORRYYRGYRRORGYOYYROROROGGRORG\t85\t0:00:00.002991\n",
      "YORYOYOORYYGYROOGGGGROORRYYRGYRRORGYOYYROROROGGRORG\t85\t0:00:00.002991\n",
      "YORYOYOORYYGYROOGGGGROORRYYRGYRRORGYOYYYOROROGGRORG\t85\t0:00:00.002991\n",
      "YORYOYRORYYGYROOGGGGROORRYYRGYRRORGYOYYYOROROGGRORG\t85\t0:00:00.002991\n",
      "YORYOYRORYYGYROOGGGGROORRYYRGYRRORGYOYYYOROROGGRGRG\t87\t0:00:00.002991\n",
      "YORYOYRORYYGYROOGGGGROORRYYRGYRRORGYOYGYOROROGGRGRG\t87\t0:00:00.002991\n",
      "YORYOYRORYYGYROOGGGGROOORYYRGYRRORGYOYGYOROROGGRGRG\t88\t0:00:00.003989\n",
      "YOOYOYRORYYGYROOGGGGROOORYYRGYRRORGYOYGYOROROGGRGRG\t88\t0:00:00.003989\n",
      "YOOYOYRORYYGYROOGGGGROOORYYRGYRRORGYOYGYOROROGGRGOG\t89\t0:00:00.003989\n",
      "YOOYOYRORYYGYROOGGGGROOORYYRGYRRORGYOYGOOROROGGRGOG\t89\t0:00:00.003989\n",
      "YOOYOYRORGYGYROOGGGGROOORYYRGYRRORGYOYGOOROROGGRGOG\t90\t0:00:00.003989\n",
      "YOOYOYROGGYGYROOGGGGROOORYYRGYRRORGYOYGOOROROGGRGOG\t91\t0:00:00.003989\n",
      "YOOYOYROGGYOYROOGGGGROOORYYRGYRRORGYOYGOOROROGGRGOG\t91\t0:00:00.003989\n",
      "YOOYOYROGGYOYROOGGGGROOORYYRGYRRORGYOYGOOROROGGYGOG\t91\t0:00:00.003989\n",
      "YOOYOYROGGYOYROGGGGGROOORYYRGYRRORGYOYGOOROROGGYGOG\t92\t0:00:00.004985\n",
      "YOOYOYROGGYOYROYGGGGROOORYYRGYRRORGYOYGOOROROGGYGOG\t92\t0:00:00.004985\n",
      "YOOYOYROGGYRYROYGGGGROOORYYRGYRRORGYOYGOOROROGGYGOG\t92\t0:00:00.004985\n",
      "YOOYOYROGGYRYROYGGGGROOORYYRGYRRORGYOYGOORRROGGYGOG\t92\t0:00:00.004985\n",
      "YOOYOYROGGYRYROYGGGGROOORYYRGYRRORGYOYGOORRROGRYGOG\t93\t0:00:00.004985\n",
      "YOOYOYRYGGYRYROYGGGGROOORYYRGYRRORGYOYGOORRROGRYGOG\t93\t0:00:00.004985\n",
      "YOOYOYRYGGYRYROYGGGGROOORYYRGYRRORYYOYGOORRROGRYGOG\t95\t0:00:00.004985\n",
      "YOOYGYRYGGYRYROYGGGGROOORYYRGYRRORYYOYGOORRROGRYGOG\t95\t0:00:00.005983\n",
      "YOOYGYRYGGYRYROYGGGGROOORYYGGYRRORYYOYGOORRROGRYGOG\t95\t0:00:00.005983\n",
      "YOOYGYRYGGYRYROYGGGGROOORYYGGYRRORYYOYGOORRROGRGGOG\t96\t0:00:00.005983\n",
      "YOOYGYRYOGYRYROYGGGGROOORYYGGYRRORYYOYGOORRROGRGGOG\t97\t0:00:00.005983\n",
      "YOOYGYRYOGYRYROYGGGGROOORYYGGGRRORYYOYGOORRROGRGGOG\t97\t0:00:00.005983\n",
      "YOOYGYRYOGYRYROYGGGGRORORYYGGGRRORYYOYGOORRROGRGGOG\t97\t0:00:00.005983\n",
      "YOGYGYRYOGYRYROYGGGGRORORYYGGGRRORYYOYGOORRROGRGGOG\t97\t0:00:00.005983\n",
      "YOGYGYRYOGYRYROYGGGGRORORYYGGGRRORYYOYGOORRROGYGGOG\t97\t0:00:00.006983\n",
      "YOGYGYRYOGYRYROYGGGGRORORYYGGGRRGRYYOYGOORRROGYGGOG\t98\t0:00:00.006983\n",
      "YOGYGYRYOGYRYROYGGGGRORORYYGGGRRGROYOYGOORRROGYGGOG\t99\t0:00:00.006983\n",
      "YOGYGYRYOGYRYROYGGGGRGRORYYGGGRRGROYOYGOORRROGYGGOG\t99\t0:00:00.006983\n",
      "YOGYGYRYOGYRYROYGGYGRGRORYYGGGRRGROYOYGOORRROGYGGOG\t99\t0:00:00.006983\n",
      "YOGYGYRYOGYRYROYGGYGRGRORYYOGGRRGROYOYGOORRROGYGGOG\t99\t0:00:00.006983\n",
      "YOGYGYRYOGYRYROOGGYGRGRORYYOGGRRGROYOYGOORRROGYGGOG\t99\t0:00:00.007980\n",
      "YOGYGYRYOGYRYRORGGYGRGRORYYOGGRRGROYOYGOORRROGYGGOG\t99\t0:00:00.007980\n",
      "YOGYGYRYOGYRYRORGGYGRGRORYYOGYRRGROYOYGOORRROGYGGOG\t99\t0:00:00.007980\n",
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      "YOGYGYRYOGYRYRORGGYGRGGORYYOGYRRGROYOYGOGRRROGYGGOG\t100\t0:00:00.007980\n",
      "YOGYGYRYOGYRYRORGGYGRGYORYYOGYRRGROYOYGOGRRROGYGGOG\t100\t0:00:00.007980\n",
      "YOGYGYRYOGYRYRORGGYGRGYORYYOGYRYGROYOYGOGRRROGYGGOG\t100\t0:00:00.008977\n",
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      "YOGYGYYYOGYRYRORGGYGRGYORYYOGYRRGROYOYGOGRRROGYGGOG\t100\t0:00:00.008977\n",
      "YOGYGYRYOGYRYRORGGYGRGYORYYOGYRRGROYOYGOGRRROGYGGOG\t100\t0:00:00.008977\n",
      "YOGYGYRYOGYRYRORGGYGRGYORGYOGYRRGROYOYGOGRRROGYGGOG\t100\t0:00:00.009975\n",
      "ROGYGYRYOGYRYRORGGYGRGYORGYOGYRRGROYOYGOGRRROGYGGOG\t100\t0:00:00.009975\n",
      "ROGYGYRYOGYRYRORGGYGRGYORGYOGYRRGGOYOYGOGRRROGYGGOG\t100\t0:00:00.009975\n",
      "ROGYGYRYOGYYYRORGGYGRGYORGYOGYRRGGOYOYGOGRRROGYGGOG\t100\t0:00:00.010972\n",
      "ROGYGRRYOGYYYRORGGYGRGYORGYOGYRRGGOYOYGOGRRROGYGGOG\t101\t0:00:00.010972\n",
      "ROGYGRRYOGYYYRORGGYGRYYORGYOGYRRGGOYOYGOGRRROGYGGOG\t101\t0:00:00.010972\n",
      "ROGYORRYOGYYYRORGGYGRYYORGYOGYRRGGOYOYGOGRRROGYGGOG\t102\t0:00:00.010972\n",
      "ROGYORRYOGYYYRORGGYGRYYORGYOGYRRGGOYOYGOGRRROGYOGOG\t102\t0:00:00.011967\n",
      "GOGYORRYOGYYYRORGGYGRYYORGYOGYRRGGOYOYGOGRRROGYOGOG\t102\t0:00:00.011967\n",
      "GOGYORYYOGYYYRORGGYGRYYORGYOGYRRGGOYOYGOGRRROGYOGOG\t102\t0:00:00.011967\n",
      "GOOYORYYOGYYYRORGGYGRYYORGYOGYRRGGOYOYGOGRRROGYOGOG\t102\t0:00:00.011967\n",
      "GOOYORYYYGYYYRORGGYGRYYORGYOGYRRGGOYOYGOGRRROGYOGOG\t102\t0:00:00.011967\n",
      "GOOYORYOYGYYYRORGGYGRYYORGYOGYRRGGOYOYGOGRRROGYOGOG\t102\t0:00:00.012965\n",
      "GOOYORYOYRYYYRORGGYGRYYORGYOGYRRGGOYOYGOGRRROGYOGOG\t102\t0:00:00.013962\n",
      "GOOYORYOYRYYYRORGGYGRYYORGYOGYRRGGOYOYGOGRYROGYOGOG\t102\t0:00:00.013962\n",
      "GOGYORYOYRYYYRORGGYGRYYORGYOGYRRGGOYOYGOGRYROGYOGOG\t102\t0:00:00.014959\n",
      "GOGYORYOYRYYYRORGGYGRYYORGYOGYRRGGOROYGOGRYROGYOGOG\t102\t0:00:00.014959\n",
      "ROGYORYOYRYYYRORGGYGRYYORGYOGYRRGGOROYGOGRYROGYOGOG\t102\t0:00:00.015958\n",
      "ROGYORYOYGYYYRORGGYGRYYORGYOGYRRGGOROYGOGRYROGYOGOG\t102\t0:00:00.015958\n",
      "ROGYORYOYGYYYRORGGYGRYYORGYOGYRRGGORYYGOGRYROGYOGOG\t102\t0:00:00.015958\n",
      "ROGYORYOYGYYYRORGGYGRYYORGYOGYRRGGORYYGOGRRROGYOGOG\t102\t0:00:00.015958\n",
      "ROGYORYOYGYRYRORGGYGRYYORGYOGYRRGGORYYGOGRRROGYOGOG\t102\t0:00:00.016957\n",
      "ROGYORYOYGYRYROROGYGRYYORGYOGYRRGGORYYGOGRRROGYOGOG\t102\t0:00:00.016957\n",
      "ROGYORYOYGYRYROROGYGRYYORGOOGYRRGGORYYGOGRRROGYOGOG\t102\t0:00:00.016957\n",
      "YOGYORYOYGYRYROROGYGRYYORGOOGYRRGGORYYGOGRRROGYOGOG\t102\t0:00:00.016957\n",
      "YOOYORYOYGYRYROROGYGRYYORGOOGYRRGGORYYGOGRRROGYOGOG\t103\t0:00:00.016957\n",
      "YOOYORYOYRYRYROROGYGRYYORGOOGYRRGGORYYGOGRRROGYOGOG\t103\t0:00:00.017962\n",
      "YOOYORYOORYRYROROGYGRYYORGOOGYRRGGORYYGOGRRROGYOGOG\t103\t0:00:00.017962\n",
      "ROOYORYOORYRYROROGYGRYYORGOOGYRRGGORYYGOGRRROGYOGOG\t103\t0:00:00.017962\n",
      "ROOYORYOORYRYROROGYGRYYORGOOGYRRGGORYYGRGRRROGYOGOG\t103\t0:00:00.017962\n",
      "ROOYORYOORYOYROROGYGRYYORGOOGYRRGGORYYGRGRRROGYOGOG\t103\t0:00:00.018948\n",
      "ROOYORYOORYOYROROGYGROYORGOOGYRRGGORYYGRGRRROGYOGOG\t103\t0:00:00.018948\n",
      "ROOYORYOORYOYROYOGYGROYORGOOGYRRGGORYYGRGRRROGYOGOG\t103\t0:00:00.019954\n",
      "ROOYORYOORYOYROYOGYGROYORGOOGYRRGGORYYGOGRRROGYOGOG\t103\t0:00:00.019954\n",
      "GOOYORYOORYOYROYOGYGROYORGOOGYRRGGORYYGOGRRROGYOGOG\t103\t0:00:00.019954\n",
      "GOOYORYOOGYOYROYOGYGROYORGOOGYRRGGORYYGOGRRROGYOGOG\t103\t0:00:00.019954\n",
      "GOOYORROOGYOYROYOGYGROYORGOOGYRRGGORYYGOGRRROGYOGOG\t103\t0:00:00.019954\n",
      "GOOYORROOGYOYROYOGYGROYORGOOGYRRGGORYYGOGRRROYYOGOG\t104\t0:00:00.020943\n",
      "GOOYORROOGYOYROYOGYGROYORGOOGGRRGGORYYGOGRRROYYOGOG\t104\t0:00:00.022938\n",
      "GOOYORROOGYOYROGOGYGROYORGOOGGRRGGORYYGOGRRROYYOGOG\t104\t0:00:00.023936\n",
      "GOOYORROOGYOYROGOGYGROYORGOOGORRGGORYYGOGRRROYYOGOG\t104\t0:00:00.023936\n",
      "GOOYORROOGYOYROGOGYGROYORGYOGORRGGORYYGOGRRROYYOGOG\t104\t0:00:00.023936\n",
      "GOORORROOGYOYROGOGYGROYORGYOGORRGGORYYGOGRRROYYOGOG\t104\t0:00:00.023936\n",
      "GOORORROOGYOYROGOGYGROYORGYOGORRGGORYYGYGRRROYYOGOG\t104\t0:00:00.024932\n",
      "GOORORROOGYOYROGOGYGROYORGOOGORRGGORYYGYGRRROYYOGOG\t104\t0:00:00.024932\n",
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      "GOORORROOGYGYROGOGYGRYYORGOOGORRGGORYYGYRRRROYYOGOG\t104\t0:00:00.025930\n",
      "GOORORROOGYGYROGOGYGRYYORGOOGGRRGGORYYGYRRRROYYOGOG\t104\t0:00:00.025930\n",
      "GOORORROOGYGYROGOGYGRYYORGOOGGRYGGORYYGYRRRROYYOGOG\t104\t0:00:00.026927\n",
      "GOORORROOGYGYROGOGYGRGYORGOOGGRYGGORYYGYRRRROYYOGOG\t104\t0:00:00.026927\n",
      "GOORORROOGYGYROGOGYGRGYORGOOGGRYGGORYYGYRRRROYYOROG\t104\t0:00:00.026927\n",
      "GOORORROOGYGYROGOGYGRGYORGOOGGRYGGORYYGYRRRROYYGROG\t104\t0:00:00.026927\n",
      "GOORORROOGYGYROGOGYGRGYORGOOGGRYGGORYYGYGRRROYYGROG\t104\t0:00:00.026927\n",
      "GOORORROOGYYYROGOGYGRGYORGOOGGRYGGORYYGYGRRROYYGROG\t104\t0:00:00.027924\n",
      "GOORORROOGYYYROOOGYGRGYORGOOGGRYGGORYYGYGRRROYYGROG\t104\t0:00:00.028922\n",
      "GOORORROOGYYYROOOGYGRGYORGOOGGRYGGORYYGYGRRRYYYGROG\t104\t0:00:00.028922\n",
      "GOORORROOGYYYROOOGYGRGYORGOOGGRYGGORYYGOGRRRYYYGROG\t104\t0:00:00.029919\n",
      "GOORORROOGYYYROOOGYGRGYORGOOGGRYGGORYYGOGRRRYYYGROO\t104\t0:00:00.030922\n",
      "GOORORROOGYYYROOOGYGRGYORGOOGGRYGGORYYGOGRRRYYYOROO\t104\t0:00:00.031919\n",
      "GOORORROOGYYYROOOGYGRGYORGOOGGOYGGORYYGOGRRRYYYOROO\t104\t0:00:00.031919\n",
      "GOORORROOGYYYROOOGYGRGYORGOOGGOYOGORYYGOGRRRYYYOROO\t104\t0:00:00.031919\n",
      "GOORORROOGYYYROOOGYGRGYORGOOGGRYOGORYYGOGRRRYYYOROO\t104\t0:00:00.031919\n",
      "GOORORROOGYYYROOOGYGRGYORGOOGGRYOGORYYGOGRRRYYYGROO\t104\t0:00:00.032910\n",
      "GOORORROOGYYYROROGYGRGYORGOOGGRYOGORYYGOGRRRYYYGROO\t104\t0:00:00.033908\n",
      "GOORORRGOGYYYROROGYGRGYORGOOGGRYOGORYYGOGRRRYYYGROO\t104\t0:00:00.034904\n",
      "GOORORRGOGYYYROROGYGRGYORGOOGGRROGORYYGOGRRRYYYGROO\t104\t0:00:00.034904\n",
      "GOORORRGOGYYYROROGYGRGYORGOOGGRROGORYYGOGRRRYYYGROY\t104\t0:00:00.034904\n",
      "GOORORRGYGYYYROROGYGRGYORGOOGGRROGORYYGOGRRRYYYGROY\t104\t0:00:00.034904\n",
      "GOORORRGYGYYYROROGYGRGYORGOOYGRROGORYYGOGRRRYYYGROY\t104\t0:00:00.034904\n",
      "GOORORRGYGYYYROROGYGRGYORGOOYGRROGOOYYGOGRRRYYYGROY\t104\t0:00:00.035902\n",
      "GOORORRGYGYYYROROGYGRGGORGOOYGRROGOOYYGOGRRRYYYGROY\t104\t0:00:00.035902\n",
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      "GOORORRGYGYYYROROGYGRGYORGOOYGRROGOOYYGOGRRROYYGROY\t105\t0:00:00.035902\n",
      "GOORORRGYGYYYROROGYGRGYORGOOYGRROGOOYYGYGRRROYYGROY\t105\t0:00:00.036911\n",
      "GOORORRGYGYYYROROGYGRGYORGOOYGRRGGOOYYGYGRRROYYGROY\t105\t0:00:00.036911\n",
      "GOORORRGYGYGYROROGYGRGYORGOOYGRRGGOOYYGYGRRROYYGROY\t105\t0:00:00.036911\n",
      "GOORORRGYGYGYROROGYGRGYORGOOYGRRGGORYYGYGRRROYYGROY\t105\t0:00:00.037896\n",
      "GOORORRGYGYGYROROGYGRGYORGOOYGRRGGORYYGYGRRROYYOROY\t105\t0:00:00.037896\n",
      "GOORORRGYRYGYROROGYGRGYORGOOYGRRGGORYYGYGRRROYYOROY\t105\t0:00:00.038894\n",
      "GOORORRGYRYGYROGOGYGRGYORGOOYGRRGGORYYGYGRRROYYOROY\t105\t0:00:00.038894\n",
      "GOORORROYRYGYROGOGYGRGYORGOOYGRRGGORYYGYGRRROYYOROY\t105\t0:00:00.038894\n",
      "GOORORROYRYGYROGOGYGRGYORGOOYGRRGGORYYGOGRRROYYOROY\t105\t0:00:00.038894\n",
      "GOORORROYRYGYROGOGYGRGYORGOOYGORGGORYYGOGRRROYYOROY\t105\t0:00:00.038894\n",
      "GOORORROYRYGYROGOGYGRGYORGOOGGORGGORYYGOGRRROYYOROY\t105\t0:00:00.038894\n",
      "GOORORROYRYGYROGOYYGRGYORGOOGGORGGORYYGOGRRROYYOROY\t105\t0:00:00.039892\n",
      "GOORORROYRYGYROGOYYGRGYORGOOGGORGGORYYGYGRRROYYOROY\t105\t0:00:00.039892\n",
      "GOORORROYRYGYROGOYYGRGYORGOOYGORGGORYYGYGRRROYYOROY\t105\t0:00:00.039892\n",
      "OOORORROYRYGYROGOYYGRGYORGOOYGORGGORYYGYGRRROYYOROY\t105\t0:00:00.039892\n",
      "OOORORROYRYGYROGOYYGRGYORGOOYGOROGORYYGYGRRROYYOROY\t105\t0:00:00.040906\n",
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      "OOORORROYGYGYROGOYYGRGYOGGOOYGOROGORYYGYGRRROYYOROY\t105\t0:00:00.043880\n",
      "OOORORROYGYGYROGOYYGRYYOGGOOYGOROGORYYGYGRRROYYOROY\t105\t0:00:00.043880\n",
      "GOORORROYGYGYROGOYYGRYYOGGOOYGOROGORYYGYGRRROYYOROY\t105\t0:00:00.044879\n",
      "GOORORROYGYGYROGOYYGRYYOGGOOYGOROGORYYGYGRRROGYOROY\t106\t0:00:00.044879\n",
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      "GOORORROOGYGYROGOYYGRYYOGGOOYGOYOGORYYGYGRRROGYOROY\t106\t0:00:00.044879\n",
      "YOORORROOGYGYROGOYYGRYYOGGOOYGOYOGORYYGYGRRROGYOROY\t106\t0:00:00.045876\n",
      "YOORORROOGYGYROGOYYGRYOOGGOOYGOYOGORYYGYGRRROGYOROY\t106\t0:00:00.045876\n",
      "YOORORROOGYGYROGOYYGRYOOGGOOGGOYOGORYYGYGRRROGYOROY\t106\t0:00:00.053853\n",
      "GOORORROOGYGYROGOYYGRYOOGGOOGGOYOGORYYGYGRRROGYOROY\t106\t0:00:00.053853\n",
      "GOORORROOGYGYROGOYYGRGOOGGOOGGOYOGORYYGYGRRROGYOROY\t106\t0:00:00.053853\n",
      "GOORORROOGYGYROGOYYGRGOOGGOOGGOROGORYYGYGRRROGYOROY\t106\t0:00:00.054851\n",
      "GOORORROOGYRYROGOYYGRGOOGGOOGGOROGORYYGYGRRROGYOROY\t106\t0:00:00.054851\n",
      "GOORORROOGYRYROGOYYGRGOOGGOOYGOROGORYYGYGRRROGYOROY\t106\t0:00:00.054851\n",
      "GOORORROOGYRYROGOYYGRYOOGGOOYGOROGORYYGYGRRROGYOROY\t106\t0:00:00.054851\n",
      "GOORORROOGYRYROGOYYGRYOOGGOOYGORGGORYYGYGRRROGYOROY\t106\t0:00:00.054851\n",
      "GOORORROOGYRYROGOYYGRROOGGOOYGORGGORYYGYGRRROGYOROY\t106\t0:00:00.054851\n",
      "YOORORROOGYRYROGOYYGRROOGGOOYGORGGORYYGYGRRROGYOROY\t106\t0:00:00.054851\n",
      "YOORORROOGYRYROGOYYGRROOGGOOYGORGGORYYGYGRRROGYGROY\t106\t0:00:00.055848\n",
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      "YOORORRYOGYRYROGOYYGRRYOGGOOGGORGGORYYGYGRRROGYGROY\t106\t0:00:00.058841\n",
      "GOORORRYOGYRYROGOYYGRRYOGGOOGGORGGORYYGYGRRROGYGROY\t106\t0:00:00.059839\n",
      "YOORORRYOGYRYROGOYYGRRYOGGOOGGORGGORYYGYGRRROGYGROY\t106\t0:00:00.059839\n",
      "YOORORRYOGYRYROGOYYGRRYOGGOOGGORGGORYYGYGRRROGRGROY\t106\t0:00:00.059839\n",
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      "ROORORRYOGYGYROGOYYGRRYOGGOOGGORGGORYYGYGRRROGRGROY\t106\t0:00:00.060836\n",
      "ROORORROOGYGYROGOYYGRRYOGGOOGGORGGORYYGYGRRROGRGROY\t106\t0:00:00.060836\n",
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      "GOORORROOGYGYROGOYYGRRYOGGOOGGORGGORYYGYRRRROGRGROY\t106\t0:00:00.060836\n",
      "GOORORROOGYGYROGOYYGRRYORGOOGGORGGORYYGYRRRROGRGROY\t106\t0:00:00.061832\n",
      "OOORORROOGYGYROGOYYGRRYORGOOGGORGGORYYGYRRRROGRGROY\t106\t0:00:00.062838\n",
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      "OOORORROOGYYYROGOYYGRROORGOOGGORGGORYYGYRRRROGRGROY\t106\t0:00:00.064826\n",
      "OOORORROOGYYYROGOYYGRYOORGOOGGORGGORYYGYRRRROGRGROY\t106\t0:00:00.065822\n",
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      "OOORORROYRYYYROGOYYGRGOORGOOGGORGGYRYYGYRRRROGRGROY\t106\t0:00:00.067817\n",
      "OOORORROORYYYROGOYYGRGOORGOOGGORGGYRYYGYRRRROGRGROY\t106\t0:00:00.067817\n",
      "OOORORROORYYYROGOYYGRYOORGOOGGORGGYRYYGYRRRROGRGROY\t106\t0:00:00.068814\n",
      "OOORORROORYYYROGOYYGYYOORGOOGGORGGYRYYGYRRRROGRGROY\t106\t0:00:00.068814\n",
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      "YOOYRRROORYYYROGOYYGYGYGRGGOYGORGGORYYGYGRRROGRGROY\t106\t0:00:00.073800\n",
      "YOOYRRROORYYYROGOYYGYGYGRGGOYGORGGORYOGYGRRROGRGROY\t106\t0:00:00.073800\n",
      "YOOYRRROORYOYROGOYYGYGYGRGGOYGORGGORYOGYGRRROGRGROY\t106\t0:00:00.073800\n",
      "GOOYRRROORYOYROGOYYGYGYGRGGOYGORGGORYOGYGRRROGRGROY\t106\t0:00:00.073800\n",
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      "GOOYRRROOGYGYROGOYYGYGYGRGGOYGORGGORYOGYGRRROGRGROY\t106\t0:00:00.074798\n",
      "GOOYRRROOGYGYROGOYYGYGYGRGGOYGORGGYRYOGYGRRROGRGROY\t106\t0:00:00.074798\n",
      "GOOYRRROOGYGYROGOYYGYGYGRGGOYGORGGYRYOGYGORROGRGROY\t106\t0:00:00.075795\n",
      "GOOYRRROOGYGYROGOYYGYGYGRGGOYGORGGORYOGYGORROGRGROY\t106\t0:00:00.075795\n",
      "GOOYRRROOGYGYROGOYYGYGOGRGGOYGORGGORYOGYGORROGRGROY\t106\t0:00:00.076795\n",
      "GOOYRRROOGYGYROGOYYGYGOGRGGORGORGGORYOGYGORROGRGROY\t106\t0:00:00.076795\n",
      "YOOYRRROOGYGYROGOYYGYGOGRGGORGORGGORYOGYGORROGRGROY\t106\t0:00:00.076795\n",
      "GOOYRRROOGYGYROGOYYGYGOGRGGORGORGGORYOGYGORROGRGROY\t106\t0:00:00.077790\n",
      "GOOYRRROOGYGYROGOYYGYGOGRGGORGORGGORYOGYRORROGRGROY\t106\t0:00:00.077790\n",
      "GOOYRRROOGYGYROGOYYGYGOGRGGOYGORGGORYOGYRORROGRGROY\t106\t0:00:00.077790\n",
      "GOOYRRROOGYGYROGOYYGYGOGRGGOYGORGGORYOGYGORROGRGROY\t106\t0:00:00.077790\n",
      "GOOYRRROOGYGYROGOYYGYROGRGGOYGORGGORYOGYGORROGRGROY\t106\t0:00:00.078787\n",
      "ROOYRRROOGYGYROGOYYGYROGRGGOYGORGGORYOGYGORROGRGROY\t106\t0:00:00.078787\n",
      "YOOYRRROOGYGYROGOYYGYROGRGGOYGORGGORYOGYGORROGRGROY\t106\t0:00:00.078787\n",
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      "YOOYRRROOGYGYROGOYYGYROGRGGOYGOROGORYYGOGORROGRGROY\t106\t0:00:00.079785\n",
      "YOOYRRROOGYGYROGOYYGYYOGRGGOYGOROGORYYGOGORROGRGROY\t106\t0:00:00.079785\n",
      "YOOYRRROOGYGYROGOYYGYYOGRGGOYGOROGORYYGORORROGRGROY\t106\t0:00:00.079785\n",
      "YOOYRRROOGYGYROGOYYGYYOGRGGOYGOROGORYYGORORROGYGROY\t106\t0:00:00.080782\n",
      "YOOYRRROOGYGYROGOYYGYYOGRGGOYGOROGORYYGOGORROGYGROY\t106\t0:00:00.080782\n",
      "YOOYORROOGYGYROGOYYGYYOGRGGOYGOROGORYYGOGORROGYGROY\t106\t0:00:00.080782\n",
      "YOOYORROOGYGYROGOYYGYROGRGGOYGOROGORYYGOGORROGYGROY\t106\t0:00:00.080782\n",
      "YOOYORROOGYYYROGOYYGYROGRGGOYGOROGORYYGOGORROGYGROY\t106\t0:00:00.081779\n",
      "YOOYORROOGYYYROGOYYGYROGRGGORGOROGORYYGOGORROGYGROY\t106\t0:00:00.081779\n",
      "YOORORROOGYYYROGOYYGYROGRGGORGOROGORYYGOGORROGYGROY\t106\t0:00:00.081779\n",
      "GOORORROOGYYYROGOYYGYROGRGGORGOROGORYYGOGORROGYGROY\t106\t0:00:00.081779\n",
      "GOORORROOGYYYROGOYYGYGOGRGGORGOROGORYYGOGORROGYGROY\t106\t0:00:00.081779\n",
      "GOORORRROGYYYROGOYYGYGOGRGGORGOROGORYYGOGORROGYGROY\t106\t0:00:00.082776\n",
      "GOORORRROGYYYROGOYYGYROGRGGORGOROGORYYGOGORROGYGROY\t106\t0:00:00.082776\n",
      "OOORORRROGYYYROGOYYGYROGRGGORGOROGORYYGOGORROGYGROY\t106\t0:00:00.084772\n",
      "OOORORRROGYYYROGOYYGYYOGRGGORGOROGORYYGOGORROGYGROY\t106\t0:00:00.085768\n",
      "OOORORRROGYYYROGOYYGYGOGRGGORGOROGORYYGOGORROGYGROY\t106\t0:00:00.085768\n",
      "OOORORRROGYYYROGOYYGYGOGRGGORGOYOGORYYGOGORROGYGROY\t106\t0:00:00.085768\n",
      "OOORORRROGYYYROGOYYGYGOGRGGORGOYOGORYYGOGORROGYOROY\t106\t0:00:00.086766\n",
      "GOORORRROGYYYROGOYYGYGOGRGGORGOYOGORYYGOGORROGYOROY\t106\t0:00:00.086766\n",
      "GOORORRROGYRYROGOYYGYGOGRGGORGOYOGORYYGOGORROGYOROY\t106\t0:00:00.086766\n",
      "ROORORRROGYRYROGOYYGYGOGRGGORGOYOGORYYGOGORROGYOROY\t106\t0:00:00.086766\n",
      "ROORORRROGYRYROGOYYGYGOGRGGORGRYOGORYYGOGORROGYOROY\t106\t0:00:00.086766\n",
      "GOORORRROGYRYROGOYYGYGOGRGGORGRYOGORYYGOGORROGYOROY\t106\t0:00:00.087763\n",
      "GOORORRROGYOYROGOYYGYGOGRGGORGRYOGORYYGOGORROGYOROY\t106\t0:00:00.087763\n",
      "GOORORRRRGYOYROGOYYGYGOGRGGORGRYOGORYYGOGORROGYOROY\t106\t0:00:00.087763\n",
      "GOORORRORGYOYROGOYYGYGOGRGGORGRYOGORYYGOGORROGYOROY\t106\t0:00:00.088760\n",
      "YOORORRORGYOYROGOYYGYGOGRGGORGRYOGORYYGOGORROGYOROY\t106\t0:00:00.088760\n",
      "YOORORRRRGYOYROGOYYGYGOGRGGORGRYOGORYYGOGORROGYOROY\t106\t0:00:00.088760\n",
      "YOORORRRRGYOYROGOYYGYGOGRGGORGRYOGORYYGOGORROGYGROY\t106\t0:00:00.090755\n",
      "ROORORRRRGYOYROGOYYGYGOGRGGORGRYOGORYYGOGORROGYGROY\t106\t0:00:00.093747\n",
      "ROORORRRRGYOYROGOYYGYGOGGGGORGRYOGORYYGOGORROGYGROY\t106\t0:00:00.093747\n",
      "ROORORRRRRYOYROGOYYGYGOGGGGORGRYOGORYYGOGORROGYGROY\t106\t0:00:00.094744\n",
      "GOORORRRRRYOYROGOYYGYGOGGGGORGRYOGORYYGOGORROGYGROY\t106\t0:00:00.095742\n",
      "GOORORRORRYOYROGOYYGYGOGGGGORGRYOGORYYGOGORROGYGROY\t106\t0:00:00.095742\n",
      "GOOYORRORRYOYROGOYYGYGOGGGGORGRYOGORYYGOGORROGYGROY\t106\t0:00:00.096739\n",
      "GOOYORRORRYOYROGOYYGYGOGRGGORGRYOGORYYGOGORROGYGROY\t106\t0:00:00.096739\n",
      "GOOYORRORRYOYROGOYYGYGOGRGGORGRYOGORYYGOGORGOGYGROY\t106\t0:00:00.096739\n",
      "GOOYORRORRYOYROGOYYGYGOGRGGORGRYOGORYYGOGORROGYGROY\t106\t0:00:00.096739\n",
      "OOOYORRORRYOYROGOYYGYGOGRGGORGRYOGORYYGOGORROGYGROY\t106\t0:00:00.096739\n",
      "OOOYRRRORRYOYROGOYYGYGOGRGGORGRYOGORYYGOGORROGYGROY\t106\t0:00:00.097736\n",
      "OOOYRRROORYOYROGOYYGYGOGRGGORGRYOGORYYGOGORROGYGROY\t106\t0:00:00.097736\n",
      "OOOYRRROORYOYROGOYYGYGOGRGGORGRYOGORYOGOGORROGYGROY\t106\t0:00:00.097736\n",
      "ROOYRRROORYOYROGOYYGYGOGRGGORGRYOGORYOGOGORROGYGROY\t106\t0:00:00.097736\n",
      "ROOYRRYOORYOYROGOYYGYGOGRGGORGRYOGORYOGOGORROGYGROY\t106\t0:00:00.097736\n",
      "YOOYRRYOORYOYROGOYYGYGOGRGGORGRYOGORYOGOGORROGYGROY\t106\t0:00:00.098734\n",
      "YOOYRRYOORYYYROGOYYGYGOGRGGORGRYOGORYOGOGORROGYGROY\t106\t0:00:00.098734\n",
      "YOOYRRYOORYYYROGOYYGYGOGRGGOYGRYOGORYOGOGORROGYGROY\t106\t0:00:00.098734\n",
      "YOOYRRYOORYYYROGOYYGYGOGRGGOYGRYOGORYOGORORROGYGROY\t106\t0:00:00.098734\n",
      "YOOYRRYOORYYYROGOYYGYGOGGGGOYGRYOGORYOGORORROGYGROY\t106\t0:00:00.099731\n",
      "YOOYRRYOOGYYYROGOYYGYGOGGGGOYGRYOGORYOGORORROGYGROY\t106\t0:00:00.099731\n",
      "YOOYRRYOOGYYYROGOYYGRGOGGGGOYGRYOGORYOGORORROGYGROY\t106\t0:00:00.099731\n",
      "YOOYRRYOOGYYYROGOYYGRGOGGGGOYRRYOGORYOGORORROGYGROY\t106\t0:00:00.099731\n",
      "YOOYRGYOOGYYYROGOYYGRGOGGGGOYRRYOGORYOGORORROGYGROY\t107\t0:00:00.099731\n"
     ]
    }
   ],
   "source": [
    "b = get_best()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1396"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "b[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "n = sorted(list(states.keys()))\n",
    "clm = {}\n",
    "for i in range(len(n)):\n",
    "    clm[n[i]] = colorLookup[b[0].Genes[i]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "us = json.load(open(\"./states.json\",\"r\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(14,8)) \n",
    "ax = plt.subplot()\n",
    "for c in us:\n",
    "    js = json.loads(us[c])\n",
    "    poly = plt.Polygon(js[\"rings\"][0],ec = '#000000',\n",
    "                           fc=clm[c], alpha = 0.8)\n",
    "    ax.add_patch(poly)\n",
    "       \n",
    "ax.set_xlim(-178,-66)\n",
    "ax.set_ylim(18,71)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
